Path planning for robots based on threat assessment and biologically inspired neural network

被引:0
作者
Dai Yalan [1 ]
Xiong Hegen [1 ]
Li Gongfa [1 ]
Nie Lei [1 ]
机构
[1] Wuhan Univ Sci & Technol, Educ Minist, Key Lab Met Equipment & Control, Wuhan, Hubei, Peoples R China
来源
2018 CHINESE AUTOMATION CONGRESS (CAC) | 2018年
基金
中国国家自然科学基金;
关键词
path planning; dynamic obstacles; virtual target; threat assessment; BINN;
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Real-time path planning for mobile robots is a very difficult and challenging problem. A new method is proposed for path planning which connected intuitionistic fuzzy set (IFS)with biologically inspired neural network(BINN) in this paper. Firstly, the virtual target helps to improve the guidance of actual target to robot. Then, according to multiple attribute decision making, the assessment model based on IFS is established to measure the threats of obstacles to robot,. Further, a novel scanning mode is presented to reduce the calculations and accelerate neuron activation. Finally, The experimental results show that the proposed BINN based on assessment method can deal with the real-time path planning problem efficiently.
引用
收藏
页码:3226 / 3231
页数:6
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